Who this is for

Includes internal models, vendor APIs, embedded AI in SaaS, open-source components, and experimental pilots accessible to more than the individual developer.

Every section below is included in your download, summaries only shown here, not the policy text.

• —

  Document control

  Owner, version, review cycle, and approval fields ready to customize.

• 1

  Purpose

  Why this policy exists and the outcomes it supports.

• 2

  Scope

  Who and what systems, locations, and activities are in scope.

• 3

  Definitions

  Key terms defined in a table for consistent interpretation.

• 4

  Roles and responsibilities

  Accountability for executives, owners, managers, staff, and IT.

• 5

  Policy requirements

  Numbered, audit-ready controls you can adopt or tailor.

• 6–8

  Exceptions, monitoring, enforcement

  Exception process, review cadence, and consequences of non-compliance.

• 9–10

  Regional compliance and framework mapping

  US, EU, and global obligations plus mapped control themes.

• A–C

  Appendices

  Customization notes, document history, and approval signatures.

Requirement themes addressed, not the verbatim policy language.

• Register every AI system before pilot or production use with mandatory metadata fields.
• Record system owner, business purpose, users, data categories, model/provider
• Assign risk classification and link to related policies (privacy, security, ADM,…
• Update inventory within five business days of material changes (new data, model swap,…
• De-register retired systems with retirement date and data disposition notes.
• Reconcile inventory quarterly against cloud billing, code repositories
• Export inventory views for auditors, regulators
• Block production deployment of unregistered high-risk AI systems via change control…
• Integrate inventory with CMDB or asset management where technically feasible.
• Review inventory data quality metrics annually and remediate gaps.